Mohammed A. Fadhel

10.9k total citations · 5 hit papers
41 papers, 6.6k citations indexed

About

Mohammed A. Fadhel is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mohammed A. Fadhel has authored 41 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 12 papers in Radiology, Nuclear Medicine and Imaging and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mohammed A. Fadhel's work include AI in cancer detection (10 papers), COVID-19 diagnosis using AI (9 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Mohammed A. Fadhel is often cited by papers focused on AI in cancer detection (10 papers), COVID-19 diagnosis using AI (9 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Mohammed A. Fadhel collaborates with scholars based in Iraq, Australia and United States. Mohammed A. Fadhel's co-authors include Laith Alzubaidi, Jinglan Zhang, Omran Al-Shamma, Ye Duan, José Santamaría, Amjad J. Humaidi, Laith Farhan, Muthana Al‐Amidie, Ayad Q. Al-Dujaili and Yuantong Gu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Expert Systems with Applications.

In The Last Decade

Mohammed A. Fadhel

41 papers receiving 6.3k citations

Hit Papers

Review of deep learning: concepts, CNN architectures, cha... 2021 2026 2022 2024 2021 2023 2023 2021 2024 1000 2.0k 3.0k 4.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
    2021 4.4k citations Laith Alzubaidi, Jinglan Zhang et al. Journal Of Big Data profile →
  2. A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
    2023 420 citations Laith Alzubaidi, Jinshuai Bai et al. Journal Of Big Data profile →
  3. A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion
    2023 372 citations A. S. Albahri, Mohammed A. Fadhel et al. Information Fusion profile →
  4. Novel Transfer Learning Approach for Medical Imaging with Limited Labeled Data
    2021 189 citations Laith Alzubaidi, Muthana Al‐Amidie et al. Cancers profile →
  5. Comprehensive systematic review of information fusion methods in smart cities and urban environments
    2024 86 citations Mohammed A. Fadhel, A. S. Albahri et al. Information Fusion profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mohammed A. Fadhel Iraq 20 2.0k 1.3k 1.1k 607 516 41 6.6k
Laith Alzubaidi Australia 27 2.2k 1.1× 1.4k 1.0× 1.2k 1.1× 672 1.1× 582 1.1× 83 7.4k
José Santamaría Spain 24 1.9k 1.0× 1.6k 1.2× 970 0.9× 639 1.1× 488 0.9× 61 6.7k
Ye Duan United States 24 1.7k 0.9× 1.6k 1.2× 1.1k 1.0× 591 1.0× 499 1.0× 120 7.2k
Omran Al-Shamma Iraq 12 1.5k 0.8× 1.1k 0.8× 946 0.9× 507 0.8× 435 0.8× 28 5.4k
Jinglan Zhang Australia 26 1.9k 1.0× 1.5k 1.1× 1.0k 0.9× 614 1.0× 528 1.0× 133 7.5k
Xiang Li China 51 2.1k 1.1× 2.2k 1.7× 1.6k 1.5× 724 1.2× 468 0.9× 409 11.3k
Laith Farhan United Kingdom 12 1.4k 0.7× 991 0.7× 720 0.7× 469 0.8× 597 1.2× 20 5.3k
Muthana Al‐Amidie United States 7 1.2k 0.6× 892 0.7× 701 0.6× 498 0.8× 458 0.9× 12 4.8k
Amjad J. Humaidi Iraq 31 1.6k 0.8× 1.4k 1.1× 748 0.7× 909 1.5× 879 1.7× 177 7.4k
Ayad Q. Al-Dujaili Iraq 11 1.2k 0.6× 876 0.7× 621 0.6× 468 0.8× 487 0.9× 43 4.8k

Countries citing papers authored by Mohammed A. Fadhel

Since Specialization
Citations

This map shows the geographic impact of Mohammed A. Fadhel's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mohammed A. Fadhel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed A. Fadhel more than expected).

Fields of papers citing papers by Mohammed A. Fadhel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed A. Fadhel. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mohammed A. Fadhel. The network helps show where Mohammed A. Fadhel may publish in the future.

Co-authorship network of co-authors of Mohammed A. Fadhel

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed A. Fadhel. A scholar is included among the top collaborators of Mohammed A. Fadhel based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohammed A. Fadhel. Mohammed A. Fadhel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Fadhel, Mohammed A., et al.. (2025). Towards unbiased skin cancer classification using deep feature fusion. BMC Medical Informatics and Decision Making. 25(1). 48–48. 4 indexed citations
2.
Fadhel, Mohammed A., et al.. (2024). Reinforcement Learning Algorithms and Applications in Healthcare and Robotics: A Comprehensive and Systematic Review. Sensors. 24(8). 2461–2461. 28 indexed citations
3.
Alzubaidi, Laith, Asma Salhi, Mohammed A. Fadhel, et al.. (2024). Trustworthy deep learning framework for the detection of abnormalities in X-ray shoulder images. PLoS ONE. 19(3). e0299545–e0299545. 19 indexed citations
4.
Fadhel, Mohammed A., et al.. (2024). Real-time diabetic foot ulcer classification based on deep learning & parallel hardware computational tools. Multimedia Tools and Applications. 83(27). 70369–70394. 12 indexed citations
5.
Fadhel, Mohammed A., et al.. (2024). New Tiger Beetle Algorithm for Cybersecurity, Medical Image Segmentation and Other Global Problems Optimization. 2024. 17–46. 8 indexed citations
6.
Alzubaidi, Laith, Mohammed A. Fadhel, Asma Salhi, et al.. (2024). SSP: self-supervised pertaining technique for classification of shoulder implants in x-ray medical images: a broad experimental study. Artificial Intelligence Review. 57(10). 10 indexed citations
7.
Alzubaidi, Laith, et al.. (2023). Reliable deep learning framework for the ground penetrating radar data to locate the horizontal variation in levee soil compaction. Engineering Applications of Artificial Intelligence. 129. 107627–107627. 24 indexed citations
8.
Fadhel, Mohammed A., et al.. (2023). Parallel processing of E-Atheer algorithm using pthread paradigm. Indonesian Journal of Electrical Engineering and Computer Science. 30(3). 1624–1624. 2 indexed citations
9.
Albahri, A. S., Mohammed A. Fadhel, Alhamzah Alnoor, et al.. (2023). A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion. Information Fusion. 96. 156–191. 372 indexed citations breakdown →
10.
Alzubaidi, Laith, Jinshuai Bai, Aiman Al-Sabaawi, et al.. (2023). A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications. Journal Of Big Data. 10(1). 420 indexed citations breakdown →
11.
Fadhel, Mohammed A., et al.. (2022). Identifying corn leaves diseases by extensive use of transfer learning: a comparative study. Indonesian Journal of Electrical Engineering and Computer Science. 29(2). 1030–1030. 9 indexed citations
12.
Xiao, Zhu, Ahmed Alkhayyat, Amjad J. Humaidi, et al.. (2022). Face Recognition Based on Deep Learning and FPGA for Ethnicity Identification. Applied Sciences. 12(5). 2605–2605. 32 indexed citations
13.
Alzubaidi, Laith, Muthana Al‐Amidie, Amjad J. Humaidi, et al.. (2021). Novel Transfer Learning Approach for Medical Imaging with Limited Labeled Data. Cancers. 13(7). 1590–1590. 189 indexed citations breakdown →
14.
Farhan, Laith, et al.. (2021). Energy Efficiency for Green Internet of Things (IoT) Networks: A Survey. SHILAP Revista de lepidopterología. 1(3). 279–314. 27 indexed citations
15.
Al‐Amidie, Muthana, Amjad J. Humaidi, Ayad Q. Al-Dujaili, et al.. (2021). Robust Spectrum Sensing Detector Based on MIMO Cognitive Radios with Non-Perfect Channel Gain. Electronics. 10(5). 529–529. 8 indexed citations
16.
Nasser, Ahmed R., Ahmed Mudheher Hasan, Amjad J. Humaidi, et al.. (2021). IoT and Cloud Computing in Health-Care: A New Wearable Device and Cloud-Based Deep Learning Algorithm for Monitoring of Diabetes. Electronics. 10(21). 2719–2719. 59 indexed citations
17.
Alzubaidi, Laith, Mohammed A. Fadhel, Omran Al-Shamma, et al.. (2020). Towards a Better Understanding of Transfer Learning for Medical Imaging: A Case Study. Applied Sciences. 10(13). 4523–4523. 157 indexed citations
18.
Alzubaidi, Laith, Mohammed A. Fadhel, Omran Al-Shamma, Jinglan Zhang, & Ye Duan. (2020). Deep Learning Models for Classification of Red Blood Cells in Microscopy Images to Aid in Sickle Cell Anemia Diagnosis. Electronics. 9(3). 427–427. 123 indexed citations
19.
Alzubaidi, Laith, Omran Al-Shamma, Mohammed A. Fadhel, et al.. (2020). Optimizing the Performance of Breast Cancer Classification by Employing the Same Domain Transfer Learning from Hybrid Deep Convolutional Neural Network Model. Electronics. 9(3). 445–445. 104 indexed citations
20.
Al-Shamma, Omran, et al.. (2019). Employment of Multi-classifier and Multi-domain Features for PCG Recognition. 321–325. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Laith Alzubaidi Breakdown of academic impact, for papers by José Santamaría Breakdown of academic impact, for papers by Ye Duan Breakdown of academic impact, for papers by Omran Al-Shamma Breakdown of academic impact, for papers by Jinglan Zhang Breakdown of academic impact, for papers by Xiang Li Breakdown of academic impact, for papers by Laith Farhan Breakdown of academic impact, for papers by Muthana Al‐Amidie Breakdown of academic impact, for papers by Amjad J. Humaidi Breakdown of academic impact, for papers by Ayad Q. Al-Dujaili
Rankless by CCL
2026